Schuetz R Zamboni N Zampieri M Heinemann M Sauer U 2012 Although the network topology of metabolism is well known, understanding the principles that govern the distribution of fluxes through metabolism lags behind. Experimentally, these fluxes can be measured by (13)C-flux analysis, and there has been a long-standing interest in understanding this functional network operation from an evolutionary perspective. On the basis of (13)C-determined fluxes from nine bacteria and multi-objective optimization theory, we show that metabolism operates close to the Pareto-optimal surface of a three-dimensional space defined by competing objectives. Consistent with flux data from evolved Escherichia coli, we propose that flux states evolve under the trade-off between two principles: optimality under one given condition and minimal adjustment between conditions. These principles form the forces by which evolution shapes metabolic fluxes in microorganisms' environmental context. https://sonar.ch/global/documents/154819 eng info:eu-repo/semantics/altIdentifier/doi/10.1126/science.1216882 info:eu-repo/semantics/altIdentifier/pmid/22556256 Science (New York, N.Y.). - 2012 Adaptation, Physiological Adenosine Triphosphate Aerobiosis Algorithms Bacteria Biological Evolution Biomass Computer Simulation Escherichia coli Glucose Metabolic Networks and Pathways Models, Biological Multidimensional optimality of microbial metabolism. http://purl.org/coar/resource_type/c_6501